来自维基百科对大数据的定义.docx

来自维基百科对大数据的定义
information-sensing mobile devices, aerial sensory technologies (remote sensing), softwarmoving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set. With this difficulty, a new platform of "big data"
tools has arisen to handle sensemaking over large quantities of data, as in the Apache Hadoop Big Data Platform.
大数据通常包括在尺寸上超出常用软件工具对数据在一定的可容忍时间间隔内进行采集、管理和处理的能力的数据集。大数据的尺寸是一个不断变化的目标，截至到2012年在一个单一数据集中的数据范围从十数TB到数个PB。由于这种困难性，出现了新的“大数据“平台工具来在大量的数据中处理合理的数据，例如Apache Hadoop大数据平台。
, an open approach to Information Management, defines big data in terms of useful permutations, complexity, and difficulty to delete individual records.
，一个开放的信息管理方式，从有用的排列、复杂性和难以删除单一记录几个方面定义了大数据。
In a 2001 research report[19] and related lectures, META Group (now Gartner) analyst
Doug Laney defined data growth challenges and opportunities as being three-dimensional, . increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources). Gartner, and now much of the industry, continue to use this "3Vs" model for describing big data.[20] In 2012, Gartner updated its definition as follows: "Big Data are high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization."[21]
在2001年的研究报告和相关文献中，META Group（现在的Gartner）的分析师Doug Laney将数据增长的挑战和机遇定义成三维方式，即总量（数据量）、速度（数据进出（变化）的速度）和多样性（数据类型和数据源的范围）。Gartner和目前业界大多数（人）延续使用这种“3V“模型来描述大数据。在2012年，Gartner更新了其对大数据的定义：”大数据是具备大数据量、
高变化速度和/或高度多样新的信息资产，这些信息资产需要新型的处理方式来强化决策制定、洞察发现和处理优化。
Examples
Examples include web logs, RFID, sensor networks, social networks, social data (due to the social data revolution), Internet text and documents, Internet search indexing, call detail records, astronomy, atmospheric science, genomics, biogeochemical, biological, and other complex and often interdiscipli